检验逆向生成社会科学以研究目标对象
Examining inverse generative social science to study targets of interest
AI总结：
本文评估逆向生成社会科学（IGSS）方法，通过回顾文献及两项冲突研究，发现其在组织研究中具有潜力，能拟合复杂非线性模型并解释为社会理论，同时提供基础软件。
摘要：
我们评估了一种新兴的模拟研究方法——逆向生成社会科学（IGSS）\n\citep{Epstein23a}——该方法利用自然选择的进化力量来建模和解释复杂目标。通过回顾近期使用IGSS的论文，并将其应用于两项不同的冲突研究，我们在此评估其作为建模方法和形式理论的潜力。我们发现IGSS在组织研究中具有潜力。与大多数其他建模方法相比，IGSS提供了两大优势：1）IGSS具有将复杂非线性模型拟合到目标上的潜力；2）这些模型有潜力被解释为社会理论。本文向新受众介绍IGSS，说明其如何做出贡献，并提供可作为IGSS研究基础的软件。
英文摘要：
We assess an emerging simulation research method -- Inverse Generative Social Science (IGSS) \citep{Epstein23a} -- that harnesses the power of evolution by natural selection to model and explain complex targets. Drawing on a review of recent papers that use IGSS, and by applying it in two different studies of conflict, we here assess its potential both as a modelling approach and as formal theory. We find that IGSS has potential for research in studies of organistions. IGSS offers two huge advantages over most other approaches to modelling. 1) IGSS has the potential to fit complex non-linear models to a target and 2) the models have the potential to be interpreted as social theory. The paper presents IGSS to a new audience, illustrates how it can contribute, and provides software that can be used as a basis of an IGSS study.
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